Collaborative phone reputation system

ABSTRACT

Various systems and methods for a collaborative phone reputation system are described herein. A system for implementing a collaborative phone reputation system includes a compute device comprising: a call handling module to detect, at the compute device, an incoming call for a user of the compute device; a scoring module to determine a local probabilistic score that the incoming call is desirable for the user; and an execution module to perform an action at the compute device based on the local probabilistic score.

PRIORITY APPLICATION

This application is a continuation of U.S. application Ser. No.14/581,446, filed Dec. 23, 2014, which is incorporated herein byreference in its entirety.

TECHNICAL FIELD

Embodiments described herein generally relate to mobile devicemanagement and in particular, to a collaborative phone reputationsystem.

BACKGROUND

Telemarketers, surveyors, and other unsolicited people may attempt tocontact a person via phone. In 2003, the Federal Trade Commissioncreated the Do Not Call Registry. People could add their own phonenumbers to the Registry. Telemarketers were required to reference theRegistry and put phone numbers from the Registry on their “do not call”lists. However, even with the Registry in place, unsolicited callscontinue to be a problem. As an example, the Registry may restraintelemarketers, but does not address social engineering attacks bycriminals trying to trick end-users into giving away personal andfinancial information.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, which are not necessarily drawn to scale, like numeralsmay describe similar components in different views. Like numerals havingdifferent letter suffixes may represent different instances of similarcomponents. Some embodiments are illustrated by way of example, and notlimitation, in the figures of the accompanying drawings in which:

FIG. 1 is a schematic drawing illustrating a system, according to anembodiment;

FIG. 2 is a block diagram illustrating control flow, according to anembodiment;

FIG. 3 is a block diagram illustrating a compute device and a serversystem for implementing a collaborative phone reputation system,according to an embodiment;

FIG. 4 is a flowchart illustrating a method of implementing acollaborative phone reputation system, according to an embodiment; and

FIG. 5 is a block diagram illustrating an example machine upon which anyone or more of the techniques (e.g., methodologies) discussed herein mayperform, according to an example embodiment.

DETAILED DESCRIPTION

Systems and methods described herein provide a collaborative phonereputation system. Using the collaborative phone reputation system, auser may avoid having to receive calls from callers who have a poorreputation.

In the ten or more years after the FTC Do No Call Registry wasestablished, unsolicited calls continue to be a problem for many people.Some of the problems stem from telemarketing firms that do not abide bythe Registry. Other problems stem from the organizations and parties notcovered by the Registry, such as charities, political organizations,surveyors, and companies that had an existing relationship with thereceiving party. But the biggest threat and challenge comes fromcriminals conducting social engineering attacks. The problem isexacerbated by the prevalence of mobile phones and the resultingsituation where people have a phone on or near them at nearly every hourof the day.

Some mobile applications and services have attempted to address theproblem of unsolicited phone calls by using blacklists. A blacklist is alist of phone numbers that are suspected to be undesirable, such astelemarketers, fraudulent solicitations, scammers, or robodialers.However, many blacklist services require manual configuration andongoing maintenance. In addition, blacklist services are a simplisticmechanism where either a number is on or not on the list, and if it ison the list, the number is blocked or flagged. What is needed a moredynamic workable solution for tracking undesirable numbers.

FIG. 1 is a schematic drawing illustrating a system 100, according to anembodiment. The system 100 includes a compute device 102 and a serversystem 104, which are communicatively coupled via a network 106. Thecompute device 102 may be a device such as a smartphone, cellulartelephone, mobile phone, laptop computer, tablet computer, music player,wearable device (e.g., watch, glasses-based device, etc.), desktop,laptop, hybrid, in-wall, or other networked device. The compute device102 includes a speaker and a non-audible alert mechanism. Thenon-audible alert mechanism may be a mechanical vibration motor or anelectronic display. When in a normal mode, the compute device 102 mayalert a user of an incoming call or notification using the audible alertmechanism (e.g., a ringtone), possibly with a non-audible alert (e.g., avibration). When operating in silent mode, the compute device 102 mayalert the user with a vibration or vibration pattern, a visualnotification, or combinations of non-audible alerts.

The network 106 may include local-area networks (LAN), wide-areanetworks (WAN), wireless networks (e.g., 802.11 or cellular network),the Public Switched Telephone Network (PSTN) network, ad hoc networks,personal area networks (e.g., Bluetooth) or other combinations orpermutations of network protocols and network types. The network 106 mayinclude a single local area network (LAN) or wide-area network (WAN), orcombinations of LANs or WANs, such as the Internet. The various devicesin FIG. 1 may be coupled to the network 106 via one or more wired orwireless connections.

The server system 104 may provide a collaborative phone reputationsystem. In addition, the server system 104 may provide auxiliaryservices, such as a social network platform, a retail shopping platform,a weather forecast or history, an appointment calendar, email, textmessaging, instant messaging, voice over Internet Protocol (VOIP), orthe like.

In use, the compute device 102 may receive an incoming phone call. Thecall agent 108 intercepts the incoming phone call and analyzes it usinga variety of mechanisms in order to determine a probability that a phonecall is undesirable. Some of the factors the call agent 108 may use area relationship between the caller and recipient, a context of therecipient, relevant call history, and the phone number reputation scoreof the calling number. The call agent 108 may access a contact list 110or a call history 112, to assess the caller's identity or the frequencyof conversations with the caller. The call agent 108 may identifyaspects of the caller or the phone number based on telephone company(“telco”) switches. For example, a telco switch may be accessed todetermine whether the caller is a commercial line or a residential line.The compute device 102 may allow calls that originate from residentiallines and block calls that originate from commercial lines. Anotherfeature that may be used is an automatic number identification featureof a telecommunications network.

While generally discussed in terms of phone calls, it is understood thatthe concepts may be applied more generally to any type of communication,such as be text messages or emails in addition to phone calls, if thereis a way to map such messages to a phone number, e.g., via an addressbook or other online directories.

The call agent 108 may also access one more sensors 114. The sensor 114may be remote from the compute device 102 or incorporated into thecompute device 102. The sensor 114 may be paired with the compute device102 using a short-range wireless network, such as Bluetooth®. The sensor114 may be one of any type of sensor, including but not limited to, acamera, a posture sensor, a biometric sensor (e.g., heart rate, skintemperature, perspiration, etc.), location sensor (e.g., GPS orGLONASS), a microphone, an accelerometer, motion sensor, ambient lightsensor, or the like. While only one sensor 114 is illustrated in FIG. 1,it is understood that more than one sensor 114 may be implemented andthat some sensors may be incorporated into the compute device 102, whileother sensors may be separate from the compute device 102. Using thesensor 114, the call agent 108 may detect a context or content of aconversation, ambient sounds, motion, or the like to indicate or infer arecipient's reaction or response to parts of the conversation.

The call agent 108 may also communicate with the server system 104 toobtain a reputation of the calling phone number. The server system 104may maintain a reputation database having phone number reputation data116 for a plurality of phone numbers. The phone number reputation data116 includes a phone number and one or more reputation scores. Thereputation scores are a reflection of how desirable it is to receive acall from the phone number. Mass-dialers, such as telemarketers or otherrobodialing systems, may have phone numbers with relatively lowreputations. In contrast, individuals who only call their family membersmay have relatively high reputations. In an example, the reputationdatabase includes phone number reputation data 116 for practically allknown phone numbers in use. The reputation database may be regional,such as only for United States phone number, or international. Thereputation database may be partitioned by country calling codes, areacodes, or other regional phone number partitioning scheme.

After the call agent 108 analyzes an incoming, ongoing, or completedcall, the call agent 108 may score the interaction and push that scoreto the server system 104. The server system 104 then uses the score toupdate the reputation of the phone number. If a phone number is beingused by a telemarketer, then the phone number's reputation may declinerapidly. If later, the same phone number is assigned to a private partywho uses it responsibly, the phone number may gain reputation. Thismechanism may also work in the instance when the phone number was withone private party (e.g., a drug dealer) and then later assigned toanother private party (e.g., a software engineer), who is able torestore the reputation associated with the phone number. In this way,the phone number is able to be dynamically restored to a reputablelevel.

The server system 104 may receive scores from a large number of clients(e.g., compute devices) to modify phone number reputations. In addition,the server system 104 may perform its own diligence on numbers, such asby performing reverse phone lookups to determine whether a number isassociated with a business or individual, and perhaps whether the numberis associated with a business known for mass-dialing (e.g.,telemarketer). The server system 104 may also access another computersystem 116, such as a consumer driven website where people report thosewho abuse or ignore the FTC Registry. The server system 104 may alsoaccess another computer system 116, such as a social media site, toidentify reports of various scams or social engineering attempts anddetermine signatures of phone callers from those reports. Using thedirect report information and other derived information, the serversystem 104 may update one more phone numbers' reputation data.

Thus, the compute device 102 may receive calls, assess the desirabilityof the call, compute and assign a score to the caller, and report thescore to the server system 104, which may then update its records ofreputation data. When the compute device 102 receives a call, it mayobtain the reputation from the server system 104. This is especiallyuseful when the call is from an unknown number. The compute device 102may also assess how the user reacted to previous instances of receivingcalls from unknown numbers (e.g., did the user pick up, send tovoicemail, or disconnect?).

The call agent 108 may also screen calls using a recorded greeting. Therecorded greeting may be a recording of the user's voice or may be acomputer-generated greeting with a simulated or pre-recorded humanvoice. The call agent 108 may answer the call and play the greeting.This is sometimes necessary to provoke a response because somerobodialers may remain silent until the recipient talks, and then therobodialer either opens a line to a human operator or begins a recordedmessage. When speech is heard in response to the greeting, the callagent 108 may analyze the call using various factors, such as is thecaller a human or a recording, is the caller voice a recognized voice(e.g., someone the user has talked to before), or what keywords are usedin the conversation. For example, keywords such as “limited time offer”or “valued customer” may indicate a sales call. Further, voice analysismay be used to determine the nationality of the caller. For example,calls with caller ID blocked and having a speaker with a foreign accentmay be an indication of a scammer Voice analysis may also be used todetermine whether the caller is human or not. The call agent 108 maylook for a typical greeting, such as “Hello” and timing of furtherconversation. For example, a human will typically greet a person andthen wait for a responsive greeting, whereas a computerize voice callermay not wait for a response from the call recipient before continuingwith a script. Timing of responses or queries during a conversion,intonation, understanding of call context and content, and other indiciamay be used to distinguish a computer-generated caller from a humancaller.

Similar speech and call analysis may be performed in an ongoing call.For example, the call agent 108 may monitor an ongoing conversation andidentify keywords, context, calling number, caller's speaking accent, orother aspects of the conversation. If the call agent 108 determines thatthe call is likely a scam, the call agent 108 may trigger a notificationto the user. The notification may be provided on the compute device 102or with an auxiliary device (e.g., a wearable device being worn by theuser). The notification may be of any type of alert including, but notlimited to an audible alert, a vibration, a non-audible alert, aflashing screen or light, an electric shock, a message, etc.

FIG. 2 is a block diagram illustrating control flow 200, according to anembodiment. At stage 202, a call is received at a compute device 102.The call may be a regular phone call, a voice over Internet Protocol(VOIP) call, etc. A call agent installed on the compute device 102determine whether the caller identification exists in a contact list orhas a history with the user of the compute device 102 (operation 204).If the caller is not in the contact list, then the call agentcommunicates with the reputation server to determine whether the callingphone number is unknown (operation 206). While some phone numbers may beunknown by the reputation server, it may be more likely that the callshave caller ID blocked, in which case there is not a phone number tolook up. If the calling number is not blocked and known by thereputation server, then the reputation score is downloaded to thecompute device 102 (operation 208). Alternately, if the phone number isunknown, then the compute device 102 may screen the call by playing agreeting (operation 210) and analyzing the answer to the greeting(operation 212).

At decision block 214, the call agent computes a probabilistic score todetermine whether the incoming call is likely desirable. For example,when the caller is known, the call agent may determine the score basedon the features of the caller (e.g., name, relationship to user based onsocial networks, email, text, behavior, history of frequency of previouscommunications, current user context including location, time, day,etc.) a probabilistic score. When the caller is unknown, then the scoremay be based on the score from the reputation server or analysis of ananswer to a screening greeting. Based on the result, the call agent willeither let the call through and the phone ring (operation 216) or ignorethe call (operation 218).

If the call is ignored (operation 218), then it is determined whetherthe caller left a voicemail message (decision block 220). If there was avoicemail left, then it is analyzed (operation 222). Keywords or phrasesmay be identified in the voicemail to determine whether the call wasinteresting. The keywords, phrases, or other analysis of the voicemailmay affect the determination of a score (operation 232). The keywords orphrases may also be pushed to the cloud (e.g., reputation server) to beused as tags or other metadata on phone numbers in the reputationdatabase. If the user listens to the voicemail (decision block 224),then the user may be asked to rate the caller (operation 226). Therating may be used in combination with other factors to determine thescore (operation 232).

Turning to the other decision path, if the probabilistic score isgreater than a threshold (decision block 214), then the phone is rung(operation 216). If the user answers (decision block 228), then the callagent may analyze the user response (operation 230). Natural languageprocessing or other speech recognition may be used to monitor theconversation and determine whether the phone number's reputation shouldbe affected. The user may also be warned of the content or likelihood ofit being a scam call. For example, in the case of detecting a criminalwho is soliciting personal information, the system may be configured tounderstand content of the call and warn a user via any availablemechanism that the call may be malicious (e.g., by buzzing a wearabledevice). If the user does not answer the phone, then the flow 200 movesto operation 232 where the score is updated. The score may be updatedbased on various inputs including the user's response (e.g., answerphone, hit ignore, listens to voicemail, texts the caller in response,etc.), the context or content of the conversation, the context orcontent of the voicemail, the rating providing be the user, etc.

If the call is not personal (decision block 234), then the score may bepushed to the reputation server (operation 236). This part is importantas it allows for crowd-sourcing of the data. As a result, malicious,obnoxious, or irritating callers may be identified faster.

At the reputation server, the scores are compiled to produce a profilefor the phone number. The profile may include a score and metadata. Themetadata may include keywords, specific feedback from users, a businessname, a business type, voice characteristics, or other information toassist in identifying a caller and/or evaluating the reputation of thephone number. The profile may have an aging mechanism, such that as aphone number ages, its reputation score increases. In this way, a phonenumber with a poor reputation that has not been used for several monthsor years, may eventually return to a neutral reputation score. Theprofile may be accessible by the owner of the phone number. The ownermay use it for their own information or audit purposes. For example, acar dealership may regularly remind customers to make routine repairappointments. The car dealership's phone number may gain a negativereputation over time as people hang up on such reminder calls. The cardealership may be interested in knowing about their reputation in orderto improve their business practices.

Metadata may also be used by users of the reputation server. Forexample, phone numbers may be filtered (either whitelisted orblacklisted) based on the metadata. A person who receives a call from abank and ignores it may later provide feedback on the voicemail left,indicating that the voicemail included the terms “credit card.” As aresult, when a different user who regularly rejects calls from creditcard companies receives a call from the bank, the call agent on thedifferent user's phone may associate the “credit card” metadata tag withthe phone number and determine that the different user likely does notwant to take the phone call from the bank.

FIG. 3 is a block diagram illustrating a compute device 102 and a serversystem 104 for implementing a collaborative phone reputation system,according to an embodiment. The compute device 102 may include a callhandling module 300, a scoring module 302, and an execution module 304.

The call handling module 300 may be configured to detect, at the computedevice, an incoming call for a user of the compute device 102.

The scoring module 302 may be configured to determine a localprobabilistic score that the incoming call is desirable for the user.

The execution module 304 may be configured to perform an action at thecompute device 102 based on the local probabilistic score.

In an embodiment, to determine the local probabilistic score, thescoring module 302 is to determine that the incoming call is from aparty in a contact list of the user and increase the local probabilisticscore based on the determination that the incoming call is from theparty in the contact list. In a further embodiment, the scoring module302 is to increase the local probabilistic score based on a frequency ofcalls from the party, a modality of calls from the party, or quality ofcontact of calls from the party.

In a further embodiment, to perform the action, the execution module 304is to notify the user of the incoming call. In a further embodiment, thescoring module 302 is to analyze a user response to the notifying theuser of the incoming call and modify the local probabilistic score basedon the user response.

In an embodiment, to determine the local probabilistic score, thescoring module 302 is to determine that the incoming call is from aparty not in a contact list of the user and decrease the localprobabilistic score based on the determination that the incoming call isfrom the party not in the contact list. In a further embodiment, theincoming call includes an originating phone number, and the scoringmodule 302 is to obtain a reputation score of the originating phonenumber and modify the local probabilistic score based on the reputationscore. In a further embodiment, to obtain the reputation score, thescoring module 302 is to obtain the reputation score from a reputationserver.

In another embodiment, the incoming call is anonymized, and the callhandling module 300 is to screen the incoming call. In such anembodiment, the scoring module 302 is to modify the local probabilisticscore based on the screening. In a further embodiment, to screen theincoming call, the call handling module 300 is to play a pre-arrangedgreeting and analyze the response to the pre-arranged greeting.

In an embodiment, the local probabilistic score is less than athreshold, and to perform the action at the compute device 102 based onthe local probabilistic score, the execution module 304 is to send theincoming call to voicemail to leave a voicemail message. In a furtherembodiment, the scoring module 302 is to analyze the voicemail messageand modify the local probabilistic score based on the analysis of thevoicemail message.

In another embodiment, the scoring module 302 is to analyze a userresponse to the voicemail message and modify the local probabilisticscore based on the user response. In a further embodiment, the scoringmodule 302 is to query the user for feedback on the incoming call, afterthe user has listened to the voicemail message and modify the localprobabilistic score based on the feedback.

In an embodiment, the execution module 304 is to transmit the localprobabilistic score to a reputation server. In this way, the localprobabilistic score may be used as crowd-sourced information about thephone number.

In an embodiment, the server system 104 is communicatively coupled tothe compute device 102 and the server system 104 may be configured tomanage, in a reputation database, a plurality of reputation scores for acorresponding plurality of phone numbers. The server system 104 mayfurther be configured to receive a request from the compute device 102for a reputation score of a particular phone number and transmit thereputation score of the particular phone number to the compute device102.

In an embodiment, to manage the plurality of reputation scores, theserver system 104 is to receive local probabilistic scores from aplurality of compute devices for the particular phone number, calculatea reputation score for the particular phone number, and revise thereputation score for the particular phone number in the reputationdatabase.

In an embodiment, to manage the plurality of reputation scores, theserver system 104 is to track usage of a phone number and increase thereputation of the phone number based on the usage. For example, if overtime the phone number is not used, the reputation may be increased. Asanother example, if over time the score received from users indicatethat the phone number is being used responsibly, then the phone number'sreputation may be increased to reflect this.

Various modules (e.g., modules 300 and 302) may be incorporated orintegrated into an application that executes on the compute device 102.The application may execute in the background and collect data from thesensors and populate a database, which may be accessed by one or moreother applications. Multiple applications may be developed to use thereal-time or historical data for various purposes.

FIG. 4 is a flowchart illustrating a method 400 of implementing acollaborative phone reputation system, according to an embodiment. Atblock 402, an incoming call is detected at a compute device for a userof the compute device.

At block 404, a local probabilistic score that the incoming call isdesirable for the user is determined.

At block 406, an action is performed at the compute device based on thelocal probabilistic score.

In an embodiment, determining the local probabilistic score comprisesdetermining that the incoming call is from a party in a contact list ofthe user and increasing the local probabilistic score based on thedetermination that the incoming call is from the party in the contactlist. In a further embodiment, the method 400 includes increasing thelocal probabilistic score based on a frequency of calls from the party,a modality of calls from the party, or quality of contact of calls fromthe party.

In a further embodiment, performing the action comprises notifying theuser of the incoming call. In a further embodiment, the method 400includes analyzing a user response to the notifying the user of theincoming call and modifying the local probabilistic score based on theuser response.

In an embodiment, determining the local probabilistic score comprises:determining that the incoming call is from a party not in a contact listof the user and decreasing the local probabilistic score based on thedetermination that the incoming call is from the party not in thecontact list. In a further embodiment, the incoming call includes anoriginating phone number, and the method 400 includes obtaining areputation score of the originating phone number and modifying the localprobabilistic score based on the reputation score. In a furtherembodiment, obtaining the reputation score comprises obtaining thereputation score from a reputation server.

In an embodiment, the incoming call is anonymized, and the method 400includes screening the incoming call and modifying the localprobabilistic score based on the screening. In a further embodiment,screening the incoming call comprises playing a pre-arranged greetingand analyzing the response to the pre-arranged greeting. In a furtherembodiment, the local probabilistic score is less than a threshold, andperforming the action at the compute device based on the localprobabilistic score comprises sending the incoming call to voicemail toleave a voicemail message. In a further embodiment, the method 400includes analyzing the voicemail message and modifying the localprobabilistic score based on the analysis of the voicemail message.

In an embodiment, the method 400 includes analyzing a user response tothe voicemail message and modifying the local probabilistic score basedon the user response. In a further embodiment, the method 400 includesquerying the user for feedback on the incoming call, after the user haslistened to the voicemail message and modifying the local probabilisticscore based on the feedback.

In an embodiment, the method 400 includes transmitting the localprobabilistic score to a reputation server.

Embodiments may be implemented in one or a combination of hardware,firmware, and software. Embodiments may also be implemented asinstructions stored on a machine-readable storage device, which may beread and executed by at least one processor to perform the operationsdescribed herein. A machine-readable storage device may include anynon-transitory mechanism for storing information in a form readable by amachine (e.g., a computer). For example, a machine-readable storagedevice may include read-only memory (ROM), random-access memory (RAM),magnetic disk storage media, optical storage media, flash-memorydevices, and other storage devices and media.

Examples, as described herein, may include, or may operate on, logic ora number of components, modules, or mechanisms. Modules may be hardware,software, or firmware communicatively coupled to one or more processorsin order to carry out the operations described herein. Modules may behardware modules, and as such modules may be considered tangibleentities capable of performing specified operations and may beconfigured or arranged in a certain manner. In an example, circuits maybe arranged (e.g., internally or with respect to external entities suchas other circuits) in a specified manner as a module. In an example, thewhole or part of one or more computer systems (e.g., a standalone,client or server computer system) or one or more hardware processors maybe configured by firmware or software (e.g., instructions, anapplication portion, or an application) as a module that operates toperform specified operations. In an example, the software may reside ona machine-readable medium. In an example, the software, when executed bythe underlying hardware of the module, causes the hardware to performthe specified operations. Accordingly, the term hardware module isunderstood to encompass a tangible entity, be that an entity that isphysically constructed, specifically configured (e.g., hardwired), ortemporarily (e.g., transitorily) configured (e.g., programmed) tooperate in a specified manner or to perform part or all of any operationdescribed herein. Considering examples in which modules are temporarilyconfigured, each of the modules need not be instantiated at any onemoment in time. For example, where the modules comprise ageneral-purpose hardware processor configured using software; thegeneral-purpose hardware processor may be configured as respectivedifferent modules at different times. Software may accordingly configurea hardware processor, for example, to constitute a particular module atone instance of time and to constitute a different module at a differentinstance of time. Modules may also be software or firmware modules,which operate to perform the methodologies described herein.

FIG. 5 is a block diagram illustrating a machine in the example form ofa computer system 500, within which a set or sequence of instructionsmay be executed to cause the machine to perform any one of themethodologies discussed herein, according to an example embodiment. Inalternative embodiments, the machine operates as a standalone device ormay be connected (e.g., networked) to other machines. In a networkeddeployment, the machine may operate in the capacity of either a serveror a client machine in server-client network environments, or it may actas a peer machine in peer-to-peer (or distributed) network environments.The machine may be an onboard vehicle system, set-top box, wearabledevice, personal computer (PC), a tablet PC, a hybrid tablet, a personaldigital assistant (PDA), a mobile telephone, or any machine capable ofexecuting instructions (sequential or otherwise) that specify actions tobe taken by that machine. Further, while only a single machine isillustrated, the term “machine” shall also be taken to include anycollection of machines that individually or jointly execute a set (ormultiple sets) of instructions to perform any one or more of themethodologies discussed herein. Similarly, the term “processor-basedsystem” shall be taken to include any set of one or more machines thatare controlled by or operated by a processor (e.g., a computer) toindividually or jointly execute instructions to perform any one or moreof the methodologies discussed herein.

Example computer system 500 includes at least one processor 502 (e.g., acentral processing unit (CPU), a graphics processing unit (GPU) or both,processor cores, compute nodes, etc.), a main memory 504 and a staticmemory 506, which communicate with each other via a link 508 (e.g.,bus). The computer system 500 may further include a video display unit510, an alphanumeric input device 512 (e.g., a keyboard), and a userinterface (UI) navigation device 514 (e.g., a mouse). In one embodiment,the video display unit 510, input device 512 and UI navigation device514 are incorporated into a touch screen display. The computer system500 may additionally include a storage device 516 (e.g., a drive unit),a signal generation device 518 (e.g., a speaker), a network interfacedevice 520, and one or more sensors (not shown), such as a globalpositioning system (GPS) sensor, compass, accelerometer, or othersensor.

The storage device 516 includes a machine-readable medium 522 on whichis stored one or more sets of data structures and instructions 524(e.g., software) embodying or utilized by any one or more of themethodologies or functions described herein. The instructions 524 mayalso reside, completely or at least partially, within the main memory504, static memory 506, and/or within the processor 502 during executionthereof by the computer system 500, with the main memory 504, staticmemory 506, and the processor 502 also constituting machine-readablemedia.

While the machine-readable medium 522 is illustrated in an exampleembodiment to be a single medium, the term “machine-readable medium” mayinclude a single medium or multiple media (e.g., a centralized ordistributed database, and/or associated caches and servers) that storethe one or more instructions 524. The term “machine-readable medium”shall also be taken to include any tangible medium that is capable ofstoring, encoding or carrying instructions for execution by the machineand that cause the machine to perform any one or more of themethodologies of the present disclosure or that is capable of storing,encoding or carrying data structures utilized by or associated with suchinstructions. The term “machine-readable medium” shall accordingly betaken to include, but not be limited to, solid-state memories, andoptical and magnetic media. Specific examples of machine-readable mediainclude non-volatile memory, including but not limited to, by way ofexample, semiconductor memory devices (e.g., electrically programmableread-only memory (EPROM), electrically erasable programmable read-onlymemory (EEPROM)) and flash memory devices; magnetic disks such asinternal hard disks and removable disks; magneto-optical disks; andCD-ROM and DVD-ROM disks.

The instructions 524 may further be transmitted or received over acommunications network 526 using a transmission medium via the networkinterface device 520 utilizing any one of a number of well-knowntransfer protocols (e.g., HTTP). Examples of communication networksinclude a local area network (LAN), a wide area network (WAN), theInternet, mobile telephone networks, plain old telephone (POTS)networks, and wireless data networks (e.g., Wi-Fi, 3G, and 4G LTE/LTE-Aor WiMAX networks). The term “transmission medium” shall be taken toinclude any intangible medium that is capable of storing, encoding, orcarrying instructions for execution by the machine, and includes digitalor analog communications signals or other intangible medium tofacilitate communication of such software.

Additional Notes & Examples

Example 1 includes subject matter (such as a device, apparatus, ormachine) for implementing a collaborative phone reputation systemcomprising: a compute device comprising: a call handling module todetect, at the compute device, an incoming call for a user of thecompute device; a scoring module to determine a local probabilisticscore that the incoming call is desirable for the user; and an executionmodule to perform an action at the compute device based on the localprobabilistic score.

In Example 2, the subject matter of Example 1 may include, wherein todetermine the local probabilistic score, the scoring module is to:determine that the incoming call is from a party in a contact list ofthe user; and increase the local probabilistic score based on thedetermination that the incoming call is from the party in the contactlist.

In Example 3, the subject matter of any one of Examples 1 to 2 mayinclude, wherein the scoring module is to increase the localprobabilistic score based on a frequency of calls from the party, amodality of calls from the party, or quality of contact of calls fromthe party.

In Example 4, the subject matter of any one of Examples 1 to 3 mayinclude, wherein to perform the action, the execution module is tonotify the user of the incoming call.

In Example 5, the subject matter of any one of Examples 1 to 4 mayinclude, wherein the scoring module is to: analyze a user response tothe notifying the user of the incoming call; and modify the localprobabilistic score based on the user response.

In Example 6, the subject matter of any one of Examples 1 to 5 mayinclude, wherein to determine the local probabilistic score, the scoringmodule is to: determine that the incoming call is from a party not in acontact list of the user; and decrease the local probabilistic scorebased on the determination that the incoming call is from the party notin the contact list.

In Example 7, the subject matter of any one of Examples 1 to 6 mayinclude, wherein the incoming call includes an originating phone number,and wherein the scoring module is to: obtain a reputation score of theoriginating phone number; and modify the local probabilistic score basedon the reputation score.

In Example 8, the subject matter of any one of Examples 1 to 7 mayinclude, wherein to obtain the reputation score, the scoring module isto obtain the reputation score from a reputation server.

In Example 9, the subject matter of any one of Examples 1 to 8 mayinclude, wherein the incoming call is anonymized, and wherein the callhandling module is to screen the incoming call; and wherein the scoringmodule is to modify the local probabilistic score based on thescreening.

In Example 10, the subject matter of any one of Examples 1 to 9 mayinclude, wherein to screen the incoming call, the call handling moduleis to: play a pre-arranged greeting; and analyze the response to thepre-arranged greeting.

In Example 11, the subject matter of any one of Examples 1 to 10 mayinclude, wherein the local probabilistic score is less than a threshold,and wherein to perform the action at the compute device based on thelocal probabilistic score, the execution module is to send the incomingcall to voicemail to leave a voicemail message.

In Example 12, the subject matter of any one of Examples 1 to 11 mayinclude, wherein the scoring module is to: analyze the voicemailmessage; and modify the local probabilistic score based on the analysisof the voicemail message.

In Example 13, the subject matter of any one of Examples 1 to 12 mayinclude, wherein the scoring module is to: analyze a user response tothe voicemail message; and modify the local probabilistic score based onthe user response.

In Example 14, the subject matter of any one of Examples 1 to 13 mayinclude, wherein the scoring module is to query the user for feedback onthe incoming call, after the user has listened to the voicemail message;and modify the local probabilistic score based on the feedback.

In Example 15, the subject matter of any one of Examples 1 to 14 mayinclude, wherein the execution module is to: transmit the localprobabilistic score to a reputation server.

In Example 16, the subject matter of any one of Examples 1 to 15 mayinclude, a server system communicatively coupled to the compute device,the server system to: manage, in a reputation database, a plurality ofreputation scores for a corresponding plurality of phone numbers;receive a request from the compute device for a reputation score of aparticular phone number; and transmit the reputation score of theparticular phone number to the compute device.

In Example 17, the subject matter of any one of Examples 1 to 16 mayinclude, wherein to manage the plurality of reputation scores, theserver system is to: receive local probabilistic scores from a pluralityof compute devices for the particular phone number; calculate areputation score for the particular phone number; and revise thereputation score for the particular phone number in the reputationdatabase.

In Example 18, the subject matter of any one of Examples 1 to 17 mayinclude, wherein to manage the plurality of reputation scores, theserver system is to: track usage of a phone number; and increase thereputation of the phone number based on the usage.

Example 19 includes subject matter (such as a method, means forperforming acts, machine readable medium including instructions thatwhen performed by a machine cause the machine to performs acts, or anapparatus to perform) for implementing a collaborative phone reputationsystem comprising: detecting, at a compute device, an incoming call fora user of the compute device; determining a local probabilistic scorethat the incoming call is desirable for the user; and performing anaction at the compute device based on the local probabilistic score.

In Example 20, the subject matter of Example 19 may include, whereindetermining the local probabilistic score comprises: determining thatthe incoming call is from a party in a contact list of the user; andincreasing the local probabilistic score based on the determination thatthe incoming call is from the party in the contact list.

In Example 21, the subject matter of any one of Examples 19 to 20 mayinclude, increasing the local probabilistic score based on a frequencyof calls from the party, a modality of calls from the party, or qualityof contact of calls from the party.

In Example 22, the subject matter of any one of Examples 19 to 21 mayinclude, wherein performing the action comprises notifying the user ofthe incoming call.

In Example 23, the subject matter of any one of Examples 19 to 22 mayinclude, analyzing a user response to the notifying the user of theincoming call; and modifying the local probabilistic score based on theuser response.

In Example 24, the subject matter of any one of Examples 19 to 23 mayinclude, wherein determining the local probabilistic score comprises:determining that the incoming call is from a party not in a contact listof the user; and decreasing the local probabilistic score based on thedetermination that the incoming call is from the party not in thecontact list.

In Example 25, the subject matter of any one of Examples 19 to 24 mayinclude, wherein the incoming call includes an originating phone number,and wherein the method further comprises: obtaining a reputation scoreof the originating phone number; and modifying the local probabilisticscore based on the reputation score.

In Example 26, the subject matter of any one of Examples 19 to 25 mayinclude, wherein obtaining the reputation score comprises obtaining thereputation score from a reputation server.

In Example 27, the subject matter of any one of Examples 19 to 26 mayinclude, wherein the incoming call is anonymized, and wherein the methodfurther comprises: screening the incoming call; and modifying the localprobabilistic score based on the screening.

In Example 28, the subject matter of any one of Examples 19 to 27 mayinclude, wherein screening the incoming call comprises: playing apre-arranged greeting; and analyzing the response to the pre-arrangedgreeting.

In Example 29, the subject matter of any one of Examples 19 to 28 mayinclude, wherein the local probabilistic score is less than a threshold,and wherein performing the action at the compute device based on thelocal probabilistic score comprises sending the incoming call tovoicemail to leave a voicemail message.

In Example 30, the subject matter of any one of Examples 19 to 29 mayinclude, analyzing the voicemail message; and modifying the localprobabilistic score based on the analysis of the voicemail message.

In Example 31, the subject matter of any one of Examples 19 to 30 mayinclude, analyzing a user response to the voicemail message; andmodifying the local probabilistic score based on the user response.

In Example 32, the subject matter of any one of Examples 19 to 31 mayinclude, querying the user for feedback on the incoming call, after theuser has listened to the voicemail message; and modifying the localprobabilistic score based on the feedback.

In Example 33, the subject matter of any one of Examples 19 to 32 mayinclude, transmitting the local probabilistic score to a reputationserver.

Example 34 includes at least one machine-readable medium includinginstructions, which when executed by a machine, cause the machine toperform operations of any of the Examples 19-33.

Example 35 includes an apparatus comprising means for performing any ofthe Examples 19-33.

Example 36 includes subject matter (such as a device, apparatus, ormachine) for implementing a collaborative phone reputation systemcomprising: means for detecting, at a compute device, an incoming callfor a user of the compute device; means for determining a localprobabilistic score that the incoming call is desirable for the user;and means for performing an action at the compute device based on thelocal probabilistic score.

In Example 37, the subject matter of Example 36 may include, wherein themeans for determining the local probabilistic score comprise: means fordetermining that the incoming call is from a party in a contact list ofthe user; and means for increasing the local probabilistic score basedon the determination that the incoming call is from the party in thecontact list.

In Example 38, the subject matter of any one of Examples 36 to 37 mayinclude, means for increasing the local probabilistic score based on afrequency of calls from the party, a modality of calls from the party,or quality of contact of calls from the party.

In Example 39, the subject matter of any one of Examples 36 to 38 mayinclude, wherein the means for performing the action comprise means fornotifying the user of the incoming call.

In Example 40, the subject matter of any one of Examples 36 to 39 mayinclude, means for analyzing a user response to the notifying the userof the incoming call; and means for modifying the local probabilisticscore based on the user response.

In Example 41, the subject matter of any one of Examples 36 to 40 mayinclude, wherein the means for determining the local probabilistic scorecomprise: means for determining that the incoming call is from a partynot in a contact list of the user; and means for decreasing the localprobabilistic score based on the determination that the incoming call isfrom the party not in the contact list.

In Example 42, the subject matter of any one of Examples 36 to 41 mayinclude, wherein the incoming call includes an originating phone number,and wherein the apparatus further comprises: means for obtaining areputation score of the originating phone number; and means formodifying the local probabilistic score based on the reputation score.

In Example 43, the subject matter of any one of Examples 36 to 42 mayinclude, wherein the means for obtaining the reputation score comprisemeans for obtaining the reputation score from a reputation server.

In Example 44, the subject matter of any one of Examples 36 to 43 mayinclude, wherein the incoming call is anonymized, and wherein theapparatus further comprises: means for screening the incoming call; andmeans for modifying the local probabilistic score based on thescreening.

In Example 45, the subject matter of any one of Examples 36 to 44 mayinclude, wherein the means for screening the incoming call comprises:means for playing a pre-arranged greeting; and means for analyzing theresponse to the pre-arranged greeting.

In Example 46, the subject matter of any one of Examples 36 to 45 mayinclude, wherein the local probabilistic score is less than a threshold,and wherein the means for performing the action at the compute devicebased on the local probabilistic score comprise means for sending theincoming call to voicemail to leave a voicemail message.

In Example 47, the subject matter of any one of Examples 36 to 46 mayinclude, means for analyzing the voicemail message; and means formodifying the local probabilistic score based on the analysis of thevoicemail message.

In Example 48, the subject matter of any one of Examples 36 to 47 mayinclude, means for analyzing a user response to the voicemail message;and means for modifying the local probabilistic score based on the userresponse.

In Example 49, the subject matter of any one of Examples 36 to 48 mayinclude, means for querying the user for feedback on the incoming call,after the user has listened to the voicemail message; and means formodifying the local probabilistic score based on the feedback.

In Example 50, the subject matter of any one of Examples 36 to 49 mayinclude, means for transmitting the local probabilistic score to areputation server.

The above detailed description includes references to the accompanyingdrawings, which form a part of the detailed description. The drawingsshow, by way of illustration, specific embodiments that may bepracticed. These embodiments are also referred to herein as “examples.”Such examples may include elements in addition to those shown ordescribed. However, also contemplated are examples that include theelements shown or described. Moreover, also contemplated are examplesusing any combination or permutation of those elements shown ordescribed (or one or more aspects thereof), either with respect to aparticular example (or one or more aspects thereof), or with respect toother examples (or one or more aspects thereof) shown or describedherein.

Publications, patents, and patent documents referred to in this documentare incorporated by reference herein in their entirety, as thoughindividually incorporated by reference. In the event of inconsistentusages between this document and those documents so incorporated byreference, the usage in the incorporated reference(s) are supplementaryto that of this document; for irreconcilable inconsistencies, the usagein this document controls.

In this document, the terms “a” or “an” are used, as is common in patentdocuments, to include one or more than one, independent of any otherinstances or usages of “at least one” or “one or more.” In thisdocument, the term “or” is used to refer to a nonexclusive or, such that“A or B” includes “A but not B,” “B but not A,” and “A and B,” unlessotherwise indicated. In the appended claims, the terms “including” and“in which” are used as the plain-English equivalents of the respectiveterms “comprising” and “wherein.” Also, in the following claims, theterms “including” and “comprising” are open-ended, that is, a system,device, article, or process that includes elements in addition to thoselisted after such a term in a claim are still deemed to fall within thescope of that claim. Moreover, in the following claims, the terms“first,” “second,” and “third,” etc. are used merely as labels, and arenot intended to suggest a numerical order for their objects.

The above description is intended to be illustrative, and notrestrictive. For example, the above-described examples (or one or moreaspects thereof) may be used in combination with others. Otherembodiments may be used, such as by one of ordinary skill in the artupon reviewing the above description. The Abstract is to allow thereader to quickly ascertain the nature of the technical disclosure. Itis submitted with the understanding that it will not be used tointerpret or limit the scope or meaning of the claims. Also, in theabove Detailed Description, various features may be grouped together tostreamline the disclosure. However, the claims may not set forth everyfeature disclosed herein as embodiments may feature a subset of saidfeatures. Further, embodiments may include fewer features than thosedisclosed in a particular example Thus, the following claims are herebyincorporated into the Detailed Description, with a claim standing on itsown as a separate embodiment. The scope of the embodiments disclosedherein is to be determined with reference to the appended claims, alongwith the full scope of equivalents to which such claims are entitled.

1. (canceled)
 2. A cellular telephone computing device that is capableof communicating, when the cellular telephone computing device is inoperation, with a remote server system via at least one wirelessnetwork, the server system comprising database storage, the cellulartelephone computing device comprising: a touch screen-based userinterface; a display; at least one camera; at least one centralprocessing unit that includes multiple cores; semiconductor memory thatincludes flash memory, the semiconductor memory being capable ofstoring, at least in part, contacts information and client applicationinstructions, the client application instructions being capable of beingexecuted, at least in part, by the at least one central processing unit,the client application instructions when executed, at least in part, bythe at least one central processing unit resulting in the cellulartelephone computing device being capable of performing operationscomprising: displaying, via the display, at least one visualnotification to a user of the cellular telephone computing device of anincoming call at the cellular telephone computing device, the incomingcall being associated with a caller telephone number that is absent fromthe contacts information; displaying, via the display, at least oneother visual notification to the user, the at least one other visualnotification being to notify the user that the incoming call possibly isa scam call, the at least one other visual notification being generatedbased, at least in part, upon reputation data stored, at least in part,in the database storage and to be associated, at least in part, with thetelephone number; receiving, via the touch screen-based user interface,user input that is capable of being in response, at least in part, tothe incoming call, the user input being capable of being used to update,at least in part, the reputation data associated, at least in part, withthe telephone number; wherein: the reputation data is capable of beingbased, at least in part, upon governmental and other users' reportinformation reporting, at least in part, the telephone number as beingassociated, at least in part, with scam activity; the cellular telephonecomputing device is capable, when the cellular telephone computingdevice is in the operation, of sensing biometric data and globalpositioning system-based location data.
 3. The cellular telephonecomputing device of claim 2, wherein: the telephone number is alsocapable of being associated with an incoming text message; and thecellular telephone computing device is capable, when the cellulartelephone computing device is in the operation, of providing, at leastin part, at least one further notification to the user that the incomingtext message is a scam text message.
 4. The cellular telephone computingdevice of claim 2, wherein: the reputation data is based, at least inpart, upon reverse telephone number lookup information, country callingcode information, area code information, and whether the telephonenumber is associated with a commercial line or residential line.
 5. Thecellular telephone computing device of claim 2, wherein: the cellulartelephone computing device also comprises a vibration-based user alertmotor to provide at least one vibration alert to indicate, at least inpart, the incoming call to the user.
 6. The cellular telephone computingdevice of claim 2, wherein: the report information comprises socialmedia site-related information; and the cellular telephone computingdevice is capable, when the cellular telephone computing device is inthe operation, of sensing accelerometer information and compass-relatedinformation.
 7. The cellular telephone computing device of claim 2,wherein: the reputation data includes, at least in part, reputationlevel to be associated with the telephone number; and the reputationlevel is capable of being associated, at least in part, with probabilitythat the incoming call is the scam call.
 8. A method associated, atleast in part, with use of a cellular telephone computing device, thecellular telephone computing device being capable of communicating, whenthe cellular telephone computing device is in operation, with a remoteserver system via at least one wireless network, the server systemcomprising database storage, the cellular telephone computing devicecomprising semiconductor memory and at least one central processingunit, the semiconductor memory comprising flash memory, the at least onecentral processing unit comprising multiple cores, the methodcomprising: executing, at least in part, by the at least one centralprocessing unit, client application instructions stored, at least inpart, in the semiconductor memory, the semiconductor memory also beingcapable of storing, at least in part, contacts information, theexecuting, at least in part, of the client application instructions bythe at least one central processing unit resulting in the cellulartelephone computing device being capable of performing operationscomprising: displaying, via a display of the cellular telephonecomputing device, at least one visual notification to a user of thecellular telephone computing device of an incoming call at the cellulartelephone computing device, the incoming call being associated with acaller telephone number that is absent from the contacts information;displaying, via the display, at least one other visual notification tothe user, the at least one other visual notification being to notify theuser that the incoming call possibly is a scam call, the at least oneother visual notification being generated based, at least in part, uponreputation data stored, at least in part, in the database storage and tobe associated, at least in part, with the telephone number; receiving,via a touch screen-based user interface of the cellular telephonecomputing device, user input that is capable of being in response, atleast in part, to the incoming call, the user input being capable ofbeing used to update, at least in part, the reputation data associated,at least in part, with the telephone number; wherein: the cellulartelephone computing device comprises at least one camera; the reputationdata is capable of being based, at least in part, upon governmental andother users' report information reporting, at least in part, thetelephone number as being associated, at least in part, with scamactivity; the cellular telephone computing device is capable, when thecellular telephone computing device is in the operation, of sensingbiometric data and global positioning system-based location data.
 9. Themethod of claim 8, wherein: the telephone number is also capable ofbeing associated with an incoming text message; and the cellulartelephone computing device is capable, when the cellular telephonecomputing device is in the operation, of providing, at least in part, atleast one further notification to the user that the incoming textmessage is a scam text message.
 10. The method of claim 8, wherein: thereputation data is based, at least in part, upon reverse telephonenumber lookup information, country calling code information, area codeinformation, and whether the telephone number is associated with acommercial line or residential line.
 11. The method of claim 8, wherein:the cellular telephone computing device also comprises a vibration-baseduser alert motor to provide at least one vibration alert to indicate, atleast in part, the incoming call to the user.
 12. The method of claim 8,wherein: the report information comprises social media site-relatedinformation; and the cellular telephone computing device is capable,when the cellular telephone computing device is in the operation, ofsensing accelerometer information and compass-related information. 13.The method of claim 8, wherein: the reputation data includes, at leastin part, reputation level to be associated with the telephone number;and the reputation level is capable of being associated, at least inpart, with probability that the incoming call is the scam call.
 14. Atleast one non-transitory computer-readable memory storing clientapplication instructions capable of being executed, at least in part, byat least one central processing unit of a cellular telephone computingdevice, the cellular telephone computing device being capable ofcommunicating, when the cellular telephone computing device is inoperation, with a remote server system via at least one wirelessnetwork, the server system comprising database storage, the cellulartelephone computing device comprising semiconductor memory and at leastone central processing unit, the semiconductor memory comprising flashmemory, the at least one central processing unit comprising multiplecores, the instructions, when executed, at least in part, by the atleast one central processing unit resulting in the cellular telephonecomputing device being capable of performing operations comprising:displaying, via a display of the cellular telephone computing device, atleast one visual notification to a user of the cellular telephonecomputing device of an incoming call at the cellular telephone computingdevice, the incoming call being associated with a caller telephonenumber that is absent from contacts information stored, at least inpart, in the semiconductor memory; displaying, via the display, at leastone other visual notification to the user, the at least one other visualnotification being to notify the user that the incoming call possibly isa scam call, the at least one other visual notification being generatedbased, at least in part, upon reputation data stored, at least in part,in the database storage and to be associated, at least in part, with thetelephone number; receiving, via a touch screen-based user interface ofthe cellular telephone computing device, user input that is capable ofbeing in response, at least in part, to the incoming call, the userinput being capable of being used to update, at least in part, thereputation data associated, at least in part, with the telephone number;wherein: the cellular telephone computing device comprises at least onecamera; the reputation data is capable of being based, at least in part,upon governmental and other users' report information reporting, atleast in part, the telephone number as being associated, at least inpart, with scam activity; the cellular telephone computing device iscapable, when the cellular telephone computing device is in theoperation, of sensing biometric data and global positioning system-basedlocation data.
 15. The at least one non-transitory computer-readablememory of claim 14, wherein: the telephone number is also capable ofbeing associated with an incoming text message; and the cellulartelephone computing device is capable, when the cellular telephonecomputing device is in the operation, of providing, at least in part, atleast one further notification to the user that the incoming textmessage is a scam text message.
 16. The at least one non-transitorycomputer-readable memory of claim 14, wherein: the reputation data isbased, at least in part, upon reverse telephone number lookupinformation, country calling code information, area code information,and whether the telephone number is associated with a commercial line orresidential line.
 17. The at least one non-transitory computer-readablememory of claim 14, wherein: the cellular telephone computing devicealso comprises a vibration-based user alert motor to provide at leastone vibration alert to indicate, at least in part, the incoming call tothe user.
 18. The at least one non-transitory computer-readable memoryof claim 14, wherein: the report information comprises social mediasite-related information; and the cellular telephone computing device iscapable, when the cellular telephone computing device is in theoperation, of sensing accelerometer information and compass-relatedinformation.
 19. The at least one non-transitory computer-readablememory of claim 14, wherein: the reputation data includes, at least inpart, reputation level to be associated with the telephone number; andthe reputation level is capable of being associated, at least in part,with probability that the incoming call is the scam call.
 20. One ormore non-transitory computer-readable memories storing clientapplication instructions capable of being executed by a cellulartelephone computing device, the cellular telephone computing devicebeing capable of communicating, when the cellular telephone computingdevice is in operation, with a remote server system via one or morewireless networks, the server system comprising database storage, thecellular telephone computing device comprising semiconductor memory andone or more central processing units, the semiconductor memorycomprising flash memory, the one or more central processing unitscomprising multiple cores, the instructions, when executed, by thecellular telephone computing device resulting in the cellular telephonecomputing device being capable of performing operations comprising:displaying, via a display of the cellular telephone computing device,one or more visual notifications to a user of the cellular telephonecomputing device of an incoming call at the cellular telephone computingdevice, the incoming call being associated with a caller telephonenumber that is absent from contacts information stored in thesemiconductor memory; displaying, via the display, one or more othervisual notifications to the user, the one or more other visualnotifications being to notify the user that the incoming call possiblyis a scam call, the one or more other visual notifications beinggenerated based, at least in part, upon reputation data stored, at leastin part, in the database storage and to be associated, at least in part,with the telephone number; receiving, via a touch screen-based userinterface of the cellular telephone computing device, user input that iscapable of being in response, at least in part, to the incoming call,the user input being capable of being used to update, at least in part,the reputation data associated, at least in part, with the telephonenumber; wherein: the cellular telephone computing device comprises oneor more cameras; the reputation data is capable of being based, at leastin part, upon governmental and other users' report informationreporting, at least in part, the telephone number as being associated,at least in part, with scam activity; the cellular telephone computingdevice is capable, when the cellular telephone computing device is inthe operation, of sensing biometric data and global positioningsystem-based location data.
 21. The one or more non-transitorycomputer-readable memories of claim 20, wherein: the telephone number isalso capable of being associated with an incoming text message; thecellular telephone computing device is capable, when the cellulartelephone computing device is in the operation, of providing one or morefurther notifications to the user that the incoming text message is ascam text message; the reputation data is based, at least in part, uponreverse telephone number lookup information, country calling codeinformation, area code information, and whether the telephone number isassociated with a commercial line or residential line; the cellulartelephone computing device also comprises a vibration-based user alertmotor to provide at least one vibration alert to indicate, at least inpart, the incoming call to the user.
 22. The one or more non-transitorycomputer-readable memories of claim 20, wherein: the report informationcomprises social media site-related information; the cellular telephonecomputing device is capable, when the cellular telephone computingdevice is in the operation, of sensing accelerometer information andcompass-related information; the reputation data includes reputationlevel to be associated with the telephone number; and the reputationlevel is capable of being associated with probability that the incomingcall is the scam call.
 23. A server system that is capable ofcommunicating with a cellular telephone computing device via at leastone wireless network, the server system comprising: at least one centralprocessing unit; database storage capable of storing reputation dataassociated, at least in part, with a caller telephone number, thereputation data being capable of being based, at least in part, upongovernmental and users' report information reporting, at least in part,the telephone number as being associated, at least in part, with scamactivity; computer-readable memory capable of storing, at least in part,instructions that when executed, at least in part, by the at least onecentral processing unit result in the server system being capable ofperforming operations comprising: providing, at least in part, otherinformation to the cellular telephone computing device, the otherinformation being based, at least in part, upon the reputation data, thecellular telephone computing device being capable of displaying, via adisplay of the cellular telephone computing device, at least one visualnotification to a user of the cellular telephone computing device of anincoming call at the cellular telephone computing device, the incomingcall being associated with the caller telephone number, the callertelephone number being absent from contacts information stored at thecellular telephone computing device, the cellular telephone computingdevice also being capable of displaying, via the display, at least oneother visual notification to the user, the at least one other visualnotification being to notify the user that the incoming call possibly isa scam call, the at least one other visual notification being generatedbased, at least in part, upon the other information; updating, at leastin part, the reputation data, based at least in part upon user inputreceived, at least in part, via a touch screen-based user interface ofthe cellular telephone computing device, the user input being capable ofbeing in response, at least in part, to the incoming call; wherein: thecellular telephone computing device is capable, when the cellulartelephone computing device is in the operation, of sensing biometricdata and global positioning system-based location data; and the cellulartelephone computing device comprises at least one camera.
 24. The serversystem of claim 23, wherein: the telephone number is also capable ofbeing associated with an incoming text message; and the cellulartelephone computing device is capable, when the cellular telephonecomputing device is in the operation, of providing, at least in part,based at least in part upon the other information, at least one furthernotification to the user that the incoming text message is a scam textmessage.
 25. The server system of claim 23, wherein: the reputation datais based, at least in part, upon reverse telephone number lookupinformation, country calling code information, area code information,and whether the telephone number is associated with a commercial line orresidential line.
 26. The server system of claim 23, wherein: thecellular telephone computing device also comprises a vibration-baseduser alert motor to provide at least one vibration alert to indicate, atleast in part, the incoming call to the user.
 27. The server system ofclaim 23, wherein: the report information comprises social mediasite-related information; and the cellular telephone computing device iscapable, when the cellular telephone computing device is in theoperation, of sensing accelerometer information and compass-relatedinformation.
 28. The server system of claim 23, wherein: the reputationdata includes, at least in part, reputation level to be associated withthe telephone number; and the reputation level is capable of beingassociated, at least in part, with probability that the incoming call isthe scam call.
 29. A method implemented, at least in part, using aserver system, the server system being capable of communicating with acellular telephone computing device via at least one wireless network,the method comprising: executing, at least in part, by at least onecentral processing unit of the server system, instructions stored, atleast in part, in computer-readable memory of the server system, theexecuting, at least in part, of the instructions resulting in the serversystem being capable of performing operations comprising: storing, in adatabase storage of the server system, reputation data associated, atleast in part, with a caller telephone number, the reputation data beingcapable of being based, at least in part, upon governmental and users'report information reporting, at least in part, the telephone number asbeing associated, at least in part, with scam activity; providing, atleast in part, other information to the cellular telephone computingdevice, the other information being based, at least in part, upon thereputation data, the cellular telephone computing device being capableof displaying, via a display of the cellular telephone computing device,at least one visual notification to a user of the cellular telephonecomputing device of an incoming call at the cellular telephone computingdevice, the incoming call being associated with the caller telephonenumber, the caller telephone number being absent from contactsinformation stored at the cellular telephone computing device, thecellular telephone computing device also being capable of displaying,via the display, at least one other visual notification to the user, theat least one other visual notification being to notify the user that theincoming call possibly is a scam call, the at least one other visualnotification being generated based, at least in part, upon the otherinformation; updating, at least in part, the reputation data, based atleast in part upon user input received, at least in part, via a touchscreen-based user interface of the cellular telephone computing device,the user input being capable of being in response, at least in part, tothe incoming call; wherein: the cellular telephone computing device iscapable, when the cellular telephone computing device is in theoperation, of sensing biometric data and global positioning system-basedlocation data; and the cellular telephone computing device comprises atleast one camera.
 30. The method of claim 29, wherein: the telephonenumber is also capable of being associated with an incoming textmessage; and the cellular telephone computing device is capable, whenthe cellular telephone computing device is in the operation, ofproviding, at least in part, based at least in part upon the otherinformation, at least one further notification to the user that theincoming text message is a scam text message.
 31. The method of claim29, wherein: the reputation data is based, at least in part, uponreverse telephone number lookup information, country calling codeinformation, area code information, and whether the telephone number isassociated with a commercial line or residential line.
 32. The method ofclaim 29, wherein: the cellular telephone computing device alsocomprises a vibration-based user alert motor to provide at least onevibration alert to indicate, at least in part, the incoming call to theuser.
 33. The method of claim 29, wherein: the report informationcomprises social media site-related information; and the cellulartelephone computing device is capable, when the cellular telephonecomputing device is in the operation, of sensing accelerometerinformation and compass-related information.
 34. The method of claim 29,wherein: the reputation data includes, at least in part, reputationlevel to be associated with the telephone number; and the reputationlevel is capable of being associated, at least in part, with probabilitythat the incoming call is the scam call.
 35. At least one non-transitorycomputer-readable memory storing instructions capable of being executed,at least in part, by at least one central processing unit of a serversystem, the server system being capable of communicating with a cellulartelephone computing device via at least one wireless network, theinstructions, when executed, at least in part, by the at least onecentral processing unit resulting in the server system being capable ofperforming operations comprising: storing, in a database storage of theserver system, reputation data associated, at least in part, with acaller telephone number, the reputation data being capable of beingbased, at least in part, upon governmental and users' report informationreporting, at least in part, the telephone number as being associated,at least in part, with scam activity; providing, at least in part, otherinformation to the cellular telephone computing device, the otherinformation being based, at least in part, upon the reputation data, thecellular telephone computing device being capable of displaying, via adisplay of the cellular telephone computing device, at least one visualnotification to a user of the cellular telephone computing device of anincoming call at the cellular telephone computing device, the incomingcall being associated with the caller telephone number, the callertelephone number being absent from contacts information stored at thecellular telephone computing device, the cellular telephone computingdevice also being capable of displaying, via the display, at least oneother visual notification to the user, the at least one other visualnotification being to notify the user that the incoming call possibly isa scam call, the at least one other visual notification being generatedbased, at least in part, upon the other information; updating, at leastin part, the reputation data, based at least in part upon user inputreceived, at least in part, via a touch screen-based user interface ofthe cellular telephone computing device, the user input being capable ofbeing in response, at least in part, to the incoming call; wherein: thecellular telephone computing device is capable, when the cellulartelephone computing device is in the operation, of sensing biometricdata and global positioning system-based location data; and the cellulartelephone computing device comprises at least one camera.
 36. The atleast one non-transitory computer-readable memory of claim 35, wherein:the telephone number is also capable of being associated with anincoming text message; and the cellular telephone computing device iscapable, when the cellular telephone computing device is in theoperation, of providing, at least in part, based at least in part uponthe other information, at least one further notification to the userthat the incoming text message is a scam text message.
 37. The at leastone non-transitory computer-readable memory of claim 35, wherein: thereputation data is based, at least in part, upon reverse telephonenumber lookup information, country calling code information, area codeinformation, and whether the telephone number is associated with acommercial line or residential line.
 38. The at least one non-transitorycomputer-readable memory of claim 35, wherein: the cellular telephonecomputing device also comprises a vibration-based user alert motor toprovide at least one vibration alert to indicate, at least in part, theincoming call to the user.
 39. The at least one non-transitorycomputer-readable memory of claim 35, wherein: the report informationcomprises social media site-related information; and the cellulartelephone computing device is capable, when the cellular telephonecomputing device is in the operation, of sensing accelerometerinformation and compass-related information.
 40. The at least onenon-transitory computer-readable memory of claim 35, wherein: thereputation data includes, at least in part, reputation level to beassociated with the telephone number; and the reputation level iscapable of being associated, at least in part, with probability that theincoming call is the scam call.
 41. One or more non-transitorycomputer-readable memories storing instructions capable of beingexecuted, at least in part, by one or more central processing units of aserver system, the server system being capable of communicating with acellular telephone computing device via one or more wireless networks,the instructions, when executed, at least in part, by the one or morecentral processing units resulting in the server system being capable ofperforming operations comprising: storing, in a database storage of theserver system, reputation data associated with a caller telephonenumber, the reputation data being capable of being based, at least inpart, upon governmental and users' report information reporting, atleast in part, the telephone number as being associated with scamactivity; providing, at least in part, other information to the cellulartelephone computing device, the other information being based, at leastin part, upon the reputation data, the cellular telephone computingdevice being capable of displaying, via a display of the cellulartelephone computing device, one or more visual notifications to a userof the cellular telephone computing device of an incoming call at thecellular telephone computing device, the incoming call being associatedwith the caller telephone number, the caller telephone number beingabsent from contacts information stored at the cellular telephonecomputing device, the cellular telephone computing device also beingcapable of displaying, via the display, one or more other visualnotifications to the user, the one or more other visual notificationsbeing to notify the user that the incoming call possibly is a scam call,the one or more other visual notifications being generated based, atleast in part, upon the other information; updating, at least in part,the reputation data, based at least in part upon user input received, atleast in part, via a touch screen-based user interface of the cellulartelephone computing device, the user input being capable of being inresponse, at least in part, to the incoming call; wherein: the cellulartelephone computing device is capable, when the cellular telephonecomputing device is in the operation, of sensing biometric data andglobal positioning system-based location data; and the cellulartelephone computing device comprises at least one camera.
 42. The one ormore non-transitory computer-readable memories of claim 41, wherein: thetelephone number is also capable of being associated with an incomingtext message; the cellular telephone computing device is capable, whenthe cellular telephone computing device is in the operation, ofproviding, based at least in part upon the other information, one ormore further notifications to the user that the incoming text message isa scam text message; the reputation data is based, at least in part,upon reverse telephone number lookup information, country calling codeinformation, area code information, and whether the telephone number isassociated with a commercial line or residential line; the cellulartelephone computing device also comprises a vibration-based user alertmotor to provide at least one vibration alert to indicate, at least inpart, the incoming call to the user.
 43. The one or more non-transitorycomputer-readable memories of claim 41, wherein: the report informationcomprises social media site-related information; the cellular telephonecomputing device is capable, when the cellular telephone computingdevice is in the operation, of sensing accelerometer information andcompass-related information; the reputation data includes reputationlevel to be associated with the telephone number; and the reputationlevel is capable of being associated with probability that the incomingcall is the scam call.